The invention relates to geophysical surveying. More particularly the invention relates to geophysical surveying for resistive and/or conductive bodies. Such bodies might, for example, comprise oil, gas, methane hydrates etc. or other hydrocarbon reserves, or subterranean salt bodies.
Seismic survey techniques are well known and provide well established methods for identifying structural features in subterranean rock strata, e.g., distinct layers and potential fluid reservoirs. Seismic techniques primarily distinguish between different subterranean structures on the basis of their different mechanical properties. Thus, for example, in the context of hydrocarbon exploration, seismic techniques are generally able to readily identify relatively low-density voids which might potentially contain hydrocarbon within the rock strata. Seismic techniques are able to identify such structures with relatively good spatial resolution. For example, it would not be unusual for seismic techniques to identify structural features, such as layer boundaries in subterranean strata, at a spatial resolution on the order of 10 m or so to depths of over 1 km. However, a drawback of seismic techniques is that while they are able to readily identify rock structures which might potentially contain, e.g., hydrocarbon (hydrocarbon reservoirs), the techniques are often unable to distinguish what is in the reservoir (i.e., the pore fluids). This is especially so for pore fluids which have similar mechanical properties, such as oil and seawater. It is therefore generally necessary to employ other survey techniques to determine whether a reservoir that has been identified through seismic surveying contains oil, for example, or just aqueous pore fluids. One way of approaching this is to use electromagnetic survey techniques.
Electromagnetic (EM) techniques have become more established over recent years. EM techniques seek to distinguish oil- and water-filled reservoirs on the basis of their differing electrical properties. Thus a primary aim of EM surveying techniques is to provide estimates of electric resistivity at locations in the subterranean strata. One group of EM surveying techniques are the controlled-source EM (CSEM) survey techniques [1, 2, 3, 4, 5]. CSEM techniques involve transmitting an EM signal into the seafloor, generally using a horizontal electric dipole (HED) source (transmitter), and measuring the response at EM receivers (detectors) for a range of distances from the source (i.e. for a range of source-receiver offsets/separations). Since hydrocarbons are more resistive than seawater (e.g. hydrocarbon-bearing sediments typically have resistivities on the order of a few tens of Ωm or higher versus a few Ωm or so for water bearing sediments), the presence of a hydrocarbon-bearing reservoir will, in general, lead to stronger EM fields than would be the case if the reservoir contained only seawater. This is because the highly conducting seawater attenuates the component of the EM signal passing through the reservoir more than would be the case if the reservoir contained hydrocarbon. Conversely, the presence of relatively more conductive structures in the subterranean strata will, in general, lead to weaker EM fields seen at the detector. This is because of the increased attenuation of fields in the conductive structure. Thus an analysis of the electromagnetic fields measured during a CSEM survey, e.g., field amplitudes and phases, can in principle provide information on subterranean resistivity profiles, and hence likely reservoir content.
However, a drawback of CSEM survey techniques in some situations is that they provide results having relatively poor spatial resolution, especially compared to seismic techniques. This can arise because CSEM techniques are primarily sensitive to the transverse resistance of buried layers, i.e. for a simple 1D layered structure, the techniques are primarily sensitive to the product of the resistance of a geological layer multiplied by its thickness. Thus a thin resistive layer can give rise to a broadly similar response to a layer that is ten-times less resistive, but ten-times thicker.
FIG. 1 schematically shows profiles for a number of geophysical properties obtained using well-log data and surface-based seismic and CSEM techniques. The data are from a region in the Northern Underwater Gas Gathering Export and Treatment System (Nuggets-1) gas field in the North Sea (blocks 3/18c, 3/19a, 3/19b, 3/20a, 3124a, 3/24c and 3125a in the UK sector of the northern North Sea). Data are plotted as a function of depth (D) beneath the seafloor from around 1450 m to 1910 m at the location of a well from which the well-log data are obtained.
The left-most curve in the figure is identified as “AI (well)” and plots acoustic impedance from well-log data. This has values ranging (left to right) from around 3500 ms−1 gm−3 to 3680 ms−1 gm−3. The next curve is identified as “RI (seismic)”. This plots the seismic relative impedance (converted from time to depth). This is determined at the well location using conventional surface seismic survey techniques. The data are uncalibrated, and the lowest values, at around D=1700 m, are clipped in the plot. The curve identified as “log ρ (well)” plots resistivity as determined from well-log data. This has values ranging from around 0 to 7. The right-most curve is identified as “log ρ (CSEM)” and this plots resistivity as determined using conventional surface CSEM survey techniques. Values for resistivity range from around 1 Ωm to 12 Ωm or so for this curve.
At the well location, the Nuggets-1 gas field includes a gas-saturated sand layer at a depth of around 1700 m, and having a thickness of around 25 m. The layer appears very clearly as an increase in the well-log resistivity (“log ρ (well)”) at this depth. This is because gas has a higher resistivity than the seawater which saturating the subterranean strata elsewhere in this profile. The gas-sand layer also appears, though less clearly, in the acoustic impedance (“AI (well)”) determined in the well. The gas-sand layer is apparent here as a layer of intermediate acoustic impedance between shale layers above having lower acoustic impedance, and brine sands below having higher acoustic impedance.
Turning now to the surface derived data, it is clear from the CSEM derived vertical resistivity profile (“log ρ (CSEM)”) that the CSEM data are sensitive to the presence of the relative high-resistivity gas-sand layer. It is, however, identified with relatively poor spatial resolution. For example, the increase in the derived resistivity associated with the gas-sand layer is spread over a depth range that is around ten-times the thickness of the layer seen in the well-log data (“log ρ (well)”). This results from the above-mentioned relatively poor spatial resolution of conventionally processed CSEM data. The surface-based seismic data (“RI (seismic)”) more clearly show the presence of the gas sand layer as a clear reduction in seismic relative impedance over a range of around 20 to 30 m at the depth of the gas sand layer.
Thus FIG. 1 demonstrates the relatively poor spatial resolution associated with resistivity profiles derived from surface CSEM data, at least compared to the spatial resolution of seismic profiles obtainable from seismic surveying. It may be noted, however, that while the CSEM profile in FIG. 1 shows relatively poor spatial resolution, it nonetheless recovers the transverse resistance of the gas-sand layer well. That is to say, product of thickness and resistivity is relatively well resolved in the CSEM profile. This can be demonstrated by integrating over the increase in the CSEM profile associated with the layer (i.e., determining the area of the “bump” in the right-hand trace in FIG. 1), and dividing by the 25-m thickness of the layer identified, e.g., from the seismic data. The corresponding remapped resistivity profile is shown overlaying the well-based resistivity data (“log ρ (well)”) in FIG. 1 (the curve is not labelled in the figure). The curve representing this remapping of the CSEM profile agrees well with the well-log data.
This shows how in principle information regarding structural features in the subterranean strata can help to constrain resistivity profiles derived from CSEM surface data. This approach has been previously suggested [6, 7] as a means for in is effect improving the spatial resolution of CSEM-derived resistivity profiles. However, the present inventors have found that the problem of using structural information, e.g. from seismic surveying, to constrain CSEM data is not an easy one to solve reliably. This is because the problem is not in general uniquely solvable, and furthermore, once a solution has been determined, there is typically no ready measure of the likelihood of the solution being a good match for the subterranean strata (i.e., there is no confidence measure).
There is therefore a need for improved methods of processing CSEM data to derive subterranean resistivity profiles which take account of pre-existing structural information, e.g., from seismic surveying.